The function of vision is to extract information from the input image that can be used to achieve current goals (e.g., accurate object identification, efficient navigation). The computational structure of the visual system is commonly viewed as a hierarchy of representational levels (e.g. Marr, 1982), ranging from an early "raw" visual code to an abstract object-model representation. Visual attention is a process that intelligently selects features or objects from one or more early representations and delivers them to higher processes which then generate more abstract representations. Attention can be active and goal-directed or passive and stimulus-driven. The proposed experiments test hypotheses about the mechanisms subserving goal-directed and stimulus-driven attentional selection. In the proposed project, (1) we examine how stimulus-driven "attentional interrupts" from motion, flicker, and featural singletons are serviced by the visual system; (2) we propose a model of visual selection that incorporates a parallel random-walk mechanism, and carry out experiments to test various aspects of the model; (3) we examine how early perceptual organization mechanisms interact with attentional mechanism using a new multielement visual tracking task; and (4) we probe the representational basis for attentional selection, testing object-based and location-based accounts. The proposed experiments will provide new evidence concerning the appropriate architecture for visual selection, and will contribute to the overall objective of deriving a comprehensive theory of intermediate-level vision. In addition to its basic-research implications, such a theory is required to guide further advances in our understanding and treatment of pathologies of the visual system at all levels, including neurological disorders from closed-head injuries and stroke as well as deficits due to biochemical imbalances.